A postdoctoral fellowship position is available in computational neuroimaging of traumatic brain injury (TBI) at the University of California, San Francisco (UCSF). UCSF is a world-class academic medical center and research institution. The position can begin as early as June 1, 2019.
The successful candidate will use state-of-the-art 3T and 7T research MR scanners and MEG, as part of prospective studies of TBI, including the US nationwide TRACK-TBI longitudinal project, leveraging the largest database to date of advanced imaging in TBI. The postdoctoral fellow will have the opportunity to work closely with physicians, imaging scientists and engineers, as well as cognitive neuroscientists. The focus of the research will be on acquiring, analyzing, and integrating advanced diffusion MRI (DTI/DKI/NODDI) microstructural, connectomic, morphometric, and functional (fMRI/MEG) longitudinal imaging data on thousands of TBI patients and normative controls. The successful candidate will also have the opportunity for methodological development, especially in the areas of diffusion imaging and tractography, functional connectivity and connectomics.
Please email CV, cover letter describing research background and interests, and contact information for 2-3 references to: Pratik Mukherjee, M.D., Ph.D. Professor of Radiology and Bioengineering
Center for Molecular and Functional Imaging Department of Radiology and Biomedical Imaging University of California, San Francisco
email@example.com UCSF Box 0946
185 Berry St., Suite 350 San Francisco, CA 94107
Candidate should have a Ph.D., M.D./Ph.D. or equivalent in Cognitive Science, Neuroscience, Psychology, Biomedical Engineering, Mathematics, Computer Science or Electrical Engineering. Experience with functional MRI is required, with first-author fMRI original research publications in peer-reviewed journals preferred. Expertise with MR image processing platforms such as FSL, AFNI, SPM and/or FreeSurfer is desirable. A background in multivariate pattern analysis and machine learning as well as strong programming skills with Python, Matlab, C/C++, and/or VTK/ITK would be considered an asset. Experience with emerging neuroinformatics platforms such as BIDS, NiPy, XNAT and OpenNeuro.org would also be a plus.